Research Article | OPEN ACCESS
Speech Enhancement with Geometric Advent of Spectral Subtraction using Connected Time-Frequency Regions Noise Estimation
1Nasir Saleem, 2Sher Ali, 3Usman Khan and 4Farman Ullah
1Institute of Engineering and Technology, GU, D.I. Khan, KPK, Pakistan
2City University of Science and Technology, Peshawar, KPK, Pakistan
3University of Engineering and Technology, Kohat, KPK, Pakistan
4COMSATS Institute of IT Quaid Avenue, Wah Cantt, Punjab, Pakistan
Research Journal of Applied Sciences, Engineering and Technology 2013 6:1081-1087
Received: October 31, 2012 | Accepted: December 28, 2012 | Published: June 30, 2013
Abstract
Speech enhancement with Geometric Advent of Spectral subtraction using connected time-frequency regions noise estimation aims to de-noise or reduce background noise from the noisy speech for better quality, pleasantness and improved intelligibility. Numerous enhancement methods are proposed including spectral subtraction, subspace, statistical with different noise estimations. The traditional spectral subtraction techniques are reasonably simple to implement and suffer from musical noise. This study addresses the new approach for speech enhancement which has minimized the insufficiencies in traditional spectral subtraction algorithms using MCRA. This approach with noise estimation has been evolved with PESQ, the ITU-T standard; Frequency weighted segmental SNR and weighted spectral slope. The analysis shows that Geometric approach with time-frequency connected regions has improved results than old-fashioned spectral subtraction algorithms. The normal hearing tests has suggested that new approach has lower audible musical noise.
Keywords:
Frequency connected regions, FwSNRseg, MCRA, PESQ, speech enhancement, spectral subtraction, WSS,
Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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